There are many conventional traffic detection systems for intersection control. Conventional systems typically utilize sensors, either in the roadway itself, or positioned at a roadside location or on traffic lights proximate to the roadway. Common types of vehicular sensors are inductive coils, or loops, embedded in a road surface, and video cameras, radar sensors, acoustic sensors, and magnetometers, either in the road itself, or at either the side of a roadway or positioned higher above traffic to observe and detect vehicles in a desired area. Each type of sensor provides information used to determine a presence of vehicles in specific traffic lanes, to provide information for proper actuation of traffic signals.
These conventional detection systems are commonly set up with ‘virtual zones’, which are hand- or machine-drawn areas on an image where objects may be moving or present. Traditionally, a vehicle passes through or stops in a zone, and these zones generate an “output” when an object is detected as passing through or resting within all or part of the zone. Many detection systems are capable of detecting different types of vehicles, such as cars, trucks, bicycles, motorcycles, pedestrians, etc. This is accomplished by creating special zones within a field of view to differentiate objects, such as bicycle zones and pedestrian zones. Therefore, conventional detection systems are capable of differentiating, for example, bicycles from other types of vehicles by analyzing these special zones.
Outputs are sent to external devices or locations for use or storage, such as for example to a traffic signal controller, which performs control and timing functions based on the information provided. These outputs also provide traffic planners and engineers with information on the volume of traffic at key points in a traffic network. This information is important for comparing volumes over periods of time to help with accurate adjustment of signal timing and managing traffic flow. Current systems and methods of traffic detection provide data that results only from a count of a total number of vehicles, which may or may not include bicycles or other road users, as therefore there is no way differentiating between different types of vehicles. As the need for modified signal timing to accommodate bicyclists, pedestrians and others becomes more critical for proper traffic management, a method for separating the count of all modes of use on a thoroughfare is needed to improve the ability to accurately manage traffic environments.
Traffic planners and engineers require data on the volume of pedestrian traffic at key points in a traffic network. This data is important for comparing volumes over periods of time to help with accurate adjustment of signal timing. No current method for automatic count and data collection for pedestrian activity exists in a traffic detection system. As the need for modified signal timing to accommodate roadway users such as pedestrians becomes more critical for proper traffic management, a method for accurately identifying and counting pedestrians using a roadway intersection would greatly improve the ability to efficiently manage traffic environments.